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The cellular prion protein controls the mesenchymal-like molecular subtype and predicts disease outcome in colorectal cancer.

ABSTRACT: BACKGROUND:Comprehensive transcriptomic analyses have shown that colorectal cancer (CRC) is heterogeneous and have led to the definition of molecular subtypes among which the stem-cell, mesenchymal-like group is associated with poor prognosis. The molecular pathways orchestrating the emergence of this subtype are incompletely understood. In line with the contribution of the cellular prion protein PrPC to stemness, we hypothesize that deregulation of this protein could lead to a stem-cell, mesenchymal-like phenotype in CRC. METHODS:We assessed the distribution of the PrPC-encoding PRNP mRNA in two large CRC cohorts according to molecular classification and its association with patient survival. We developed cell-based assays to explore the impact of gain and loss of PrPC function on markers of the mesenchymal subtype and to delineate the signalling pathways recruited by PrPC. We measured soluble PrPC in the plasmas of 325 patients with metastatic CRC and probed associations with disease outcome. FINDINGS:We found that PRNP gene expression is enriched in tumours of the mesenchymal subtype and is associated with poor survival. Our in vitro analyses revealed that PrPC controls the expression of genes that specify the mesenchymal subtype through the recruitment of the Hippo pathway effectors YAP and TAZ and the TGFß pathway. We showed that plasma levels of PrPC are elevated in metastatic CRC and are associated with poor disease control. INTERPRETATION:Our findings define PrPC as a candidate driver of the poor-prognosis mesenchymal subtype of CRC. They suggest that PrPC may serve as a potential biomarker for patient stratification in CRC. FUNDING:Grant support was provided by the following: Cancéropôle Ile de France (grant number 2016-1-EMERG-36-UP 5-1), Association pour la Recherche sur le Cancer (grant number PJA 20171206220), SATT Ile de France Innov (grant number 415) as well as INSERM.

SUBMITTER: Le Corre D

PROVIDER: S-EPMC6710984 | biostudies-literature | 2019 Aug

REPOSITORIES: biostudies-literature

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The cellular prion protein controls the mesenchymal-like molecular subtype and predicts disease outcome in colorectal cancer.

Le Corre Delphine D Ghazi Alexandre A Balogoun Ralyath R Pilati Camilla C Aparicio Thomas T Martin-Lannerée Séverine S Marisa Laetitia L Djouadi Fatima F Poindessous Virginie V Crozet Carole C Emile Jean-François JF Mulot Claire C Le Malicot Karine K Boige Valérie V Blons Hélène H de Reynies Aurélien A Taieb Julien J Ghiringhelli François F Bennouna Jaafar J Launay Jean-Marie JM Laurent-Puig Pierre P Mouillet-Richard Sophie S

EBioMedicine 20190731

<h4>Background</h4>Comprehensive transcriptomic analyses have shown that colorectal cancer (CRC) is heterogeneous and have led to the definition of molecular subtypes among which the stem-cell, mesenchymal-like group is associated with poor prognosis. The molecular pathways orchestrating the emergence of this subtype are incompletely understood. In line with the contribution of the cellular prion protein PrP<sup>C</sup> to stemness, we hypothesize that deregulation of this protein could lead to ...[more]

PMID: 31377347

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Project description:Molecular subtypes of medulloblastoma [Sonic Hedgehog (SHH), Wingless/INT (WNT), Group 3, and Group 4] are defined by common patterns of gene expression. These differential gene expression patterns appear to result in different histomorphology and prognosis. Quantitative histomorphometry is a well-known method of computer-aided pathology image analysis. The hypotheses we sought to examine in this preliminary proof of concept study were whether computer extracted nuclear morphological features of medulloblastomas from digitized tissue slide images could independently: (1) distinguish between molecularly determined subgroups and (2) identify patterns within these subgroups that correspond with clinical outcome. Our dataset was composed of 46 medulloblastoma patients: 16 SHH (5 dead, 11 survived), 3 WNT (0 dead, 3 survived), 12 Group 3 (4 dead, 8 survived), and 15 were Group 4 (5 dead, 10 survived). A watershed-based thresholding scheme was used to automatically identify individual nuclei within digitized whole slide hematoxylin and eosin tissue images. Quantitative histomorphometric features corresponding to the texture (variation in pixel intensity), shape (variations in size, roundness), and architectural rearrangement (distances between, and number of connected neighbors) of nuclei were subsequently extracted. These features were ranked using feature selection schemes and these top-ranked features were then used to train machine-learning classifiers via threefold cross-validation to separate patients based on: (1) molecular subtype and (2) disease-specific outcomes within the individual molecular subtype groups. SHH and WNT tumors were separated from Groups 3 and 4 tumors with a maximum area under the receiver operating characteristic curve (AUC) of 0.7, survival within Group 3 tumors was predicted with an AUC of 0.92, and Group 3 and 4 patients were separated into high- and low-risk groups with p = 0.002. Model prediction was quantitatively compared with age, stage, and histological subtype using univariate and multivariate Cox hazard ratio models. Age was the most statistically significant variable for predicting survival in Group 3 and 4 tumors, but model predictions had the highest hazard ratio value. Quantitative nuclear histomorphometry can be used to study medulloblastoma genetic expression phenotypes as it may distinguish meaningful features of disease pathology.

Dataset Information

The cellular prion protein controls the mesenchymal-like molecular subtype and predicts disease outcome in colorectal cancer.

Publications

The cellular prion protein controls the mesenchymal-like molecular subtype and predicts disease outcome in colorectal cancer.

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